Federal and State Tax law has become so complex that it is now estimated that each year Americans alone use over 6 billion person hours, and spend nearly 4 billion dollars, in an effort to comply with Federal and State Tax statutes. Given this level of complexity and cost, it is not surprising that more and more taxpayers find it necessary to obtain help, in one form or another, to prepare their taxes. Tax return preparation systems, such as tax return preparation software programs and applications, represent a potentially flexible, highly accessible, and affordable source of tax preparation assistance. However, traditional tax return preparation systems are, by design, fairly generic in nature and often lack the malleability to meet the specific needs of a given user.
For instance, traditional tax return preparation systems often present a fixed, e.g., predetermined and pre-packaged, structure or sequence of questions to all users as part of the tax return preparation interview process. This is largely due to the fact that the traditional tax return preparation system analytics used to generate a sequence of interview questions are static features that are typically hard-coded elements of the tax return preparation system and do not lend themselves to effective or efficient modification. As an example, in traditional tax return preparation systems, the sequence of questions presented to a user is pre-determined based on a generic user model that is, in fact and by design, not accurately representative of any particular “real world” user. Consequently, irrelevant, and often confusing, interview questions are virtually always presented to any given real world user. It is therefore not surprising that many, if not all, user of these traditional tax return preparation systems experience, at best, an impersonal, unnecessarily long, confusing, and complicated, interview process and user experience. Clearly, this is not the type of impression that results in happy, loyal, repeat customers.
Even worse is the fact that, in many cases, the hard-coded and static analysis features associated with traditional tax return preparation systems, and the resulting presentation of irrelevant questioning and user experiences, leads potential users of traditional tax return preparation systems, i.e., potential customers, to believe that the tax return preparation system is not applicable to them, and perhaps is unable to meet their specific needs. In other cases, the users simply become frustrated with these irrelevant lines of questioning and other user experience elements. Many of these potential users and customers then simply abandon the process and the tax return preparation systems completely, i.e., never become paying customers. Clearly, this is an undesirable result for both the potential user of the tax return preparation system and the provider of the tax return preparation system.
What is needed is a method and system for reducing the presentation of irrelevant questions to users during a tax return preparation interview, to improve the personalization of the electronic tax return preparation interview process.